Cyanobacterial blooms deteriorate the water quality and impair the use of lakes and reservoirs. They also threaten human health through toxin production. Therefore, regular monitoring of cyanobacterial biomass is critical for bloom detection. In Karaoun Reservoir, the largest freshwater body in Lebanon, cyanobacteria have been strongly dominating phytoplankton since 2009. In their seasonal trend, Microcystis aeruginosa dominates in summer while Aphanizomenon (Chrysosporum) ovalisporum occurs in spring and autumn. The presence of these blooms hampers Karaoun reservoir services including fisheries, recreational uses and irrigation. Understanding how cyanobacteria respond to water level fluctuations and to the thermal structure of the reservoir is important for adequate management. In this study, we aim to use modelling in order to complement field monitoring and determine factors governing cyanobacteria distribution. In order to calibrate and validate the adopted model, field campaigns were conducted in 2017 and consisted of measuring cyanobacteria distribution with phycocyanin fluorescence profiles, water temperature profiles and water transparency at three locations in the reservoir. These campaigns allowed us to analyze the spatial and temporal variability of cyanobacteria distribution. We used a coupled three dimensional hydrodynamic-ecological model, the Delft 3D suite, to simulate water level fluctuations, water temperature and cyanobacterial biomass. Eventually we compared the spatial distribution of cyanobacteria from field measurements and simulation results. Model simulations helped explain the influence of hydrodynamic processes that led to observed vertical and horizontal heterogeneities of cyanobacteria. We provide a thorough discussion about the contribution of modelling techniques to this study.